model A script for static cumulant statistics

modelA_static.jl

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+cd(@__DIR__)
+
+using Distributions
+using Printf
+using Random
+using JLD2
+
+ENV["JULIA_CUDA_USE_BINARYBUILDER"] = false
+
+Random.seed!(parse(Int, ARGS[3]))
+
+const L = parse(Int, ARGS[2])
+const λ = 4.0f0
+const Γ = 1.0f0
+const T = 1.0f0
+
+const Δt = 0.04f0/Γ
+const Rate = Float32(sqrt(2.0*Δt*Γ))
+
+function ΔH(x, φ, φt, m²)
+    @inbounds φold = φ[x[1], x[2], x[3]]
+    Δφ = φt - φold
+    Δφ² = φt^2 - φold^2
+
+    @inbounds ∑nn = φ[x[1]%L+1, x[2], x[3]] + φ[x[1], x[2]%L+1, x[3]] + φ[x[1], x[2], x[3]%L+1]
+    @inbounds ∑nn += φ[(x[1]+L-2)%L+1, x[2], x[3]] + φ[x[1], (x[2]+L-2)%L+1, x[3]] + φ[x[1], x[2], (x[3]+L-2)%L+1]
+
+    3Δφ² - Δφ * ∑nn + 0.5m² * Δφ² + 0.25λ * (φt^4 - φold^4)
+end
+
+function step(m², φ, x)
+    δ = Rate*rand(Normal())
+    @inbounds φnew = φ[x[1], x[2], x[3]] + δ
+
+    P = min(1.0f0, exp(-ΔH(x, φ, φnew, m²)/T))
+    r = rand(Float32)
+    if (r < P)
+        @inbounds φ[x[1], x[2], x[3]] = φnew
+    end
+end
+
+function sweep(m², φ, L)
+	Threads.@threads for i in 1:L
+		for j in 1:L
+			for k in 1:L
+				if (i+j+k)%2 == 0
+					step(m², φ, (i,j,k))
+				end
+			end
+		end
+	end
+
+	Threads.@threads for i in 1:L
+		for j in 1:L
+			for k in 1:L
+				if (i+j+k)%2 !=0
+					step(m², φ, (i,j,k))
+				end
+			end
+		end
+	end
+end
+
+function thermalize(m², φ, L, N=10000)
+    for i in 1:N
+        sweep(m², φ, L)
+    end
+end
+
+M(φ) = 2/L^3*sum(φ[:,:,1:L÷2])
+
+# near critical value
+m² = -2.0
+
+maxt = L^2*500
+skip = 10
+batch = parse(Int, ARGS[4])
+
+for series in 1:16
+	df = load("/share/tmschaef/jkott/modelB/KZ/IC_sym_L_$L"*"_id_"*ARGS[1]*"_series_$series.jld2")
+
+	for run in (16batch-15):16batch
+		ϕ = df["ϕ"]
+
+		thermalize(m², ϕ, L, 1.5 * 10^4)
+
+		open("/share/tmschaef/jkott/modelB/KZ/cumulants/static/sum_L_$L"*"_id_"*ARGS[1]*"_series_$series"*"_run_$run.dat","w") do io 
+			for i in 0:div(maxt,skip)
+				Printf.@printf(io, "%i %f\n", i*skip, M(ϕ))
+				thermalize(m², ϕ, L, skip)
+			end
+		end
+	end
+end